Associations between maternal mental health, child dental anxiety, and oral health of 6- to 12-year-olds in Nigeria
Bibliographic record
Abstract
Maternal mental health affects their children's oral health. This study assessed the associations between maternal mental health and dental anxiety level, dental caries experience, oral hygiene, and gingival status among 6- to 12-year-old children in Nigeria. This was a cross-sectional study that recruited mother-child dyad participants through a household survey conducted in Ile-Ife, Nigeria. Data collected included the independent (maternal mental health risk, depressive symptoms, and child's dental anxiety), and dependent (caries experience, oral hygiene status, and gingival health status) variables. Multivariate logistic regression analysis was conducted to determine the associations between dependent and independent variables after adjusting for confounders (mothers' age, child's age, sex, and socioeconomic status). Statistical significance was set at p < 0.05. Of the 1411 mothers recruited, 1248 (88.4%) had low mental health risk, and 896 (63.5%) had mild depressive symptoms. As for the children, 53 (3.8%) had caries, 745 (52.8%) had moderate to high dental anxiety, 953 (63.0%) had gingivitis and 36 (2.6%) had poor oral hygiene. The maternal mental health risk was not significantly associated with the child's caries experience (AOR: 1.012; 95%CI: 0.860-1.190; p = 0.886), poor oral hygiene (AOR:1.037; 95%CI: 0.975-1.104; p=0.250), and moderate/severe gingivitis (AOR:0.887; 95%CI: 0.764-1.030; p = 0.115). Maternal depression status was not significantly associated with the child's caries experience (AOR: 0.910; 95%CI: 0.802-1.033; p = 0.145), poor oral hygiene (AOR: 1.016; 95%CI: 0.976-1.057; p = 0.439), and moderate/severe gingivitis (AOR: 0.963; 95%CI: 0.861-1.077; p = 0.509). Maternal mental health risk and depression do not seem to be risk factors for schoolchildren's oral health in Nigeria. Further studies are needed to understand these findings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".